Show simple item record

Files in this item


Item metadata

dc.contributor.authorSchlag, Karl H.
dc.contributor.authorZapechelnyuk, Andriy
dc.identifier.citationSchlag , K H & Zapechelnyuk , A 2017 , ' Dynamic benchmark targeting ' , Journal of Economic Theory , vol. 169 , pp. 145-169 .
dc.identifier.otherPURE: 249597706
dc.identifier.otherPURE UUID: b9d407a9-d5e5-43b5-b666-792c4b7b62c0
dc.identifier.otherScopus: 85013392752
dc.identifier.otherWOS: 000401394800007
dc.identifier.otherORCID: /0000-0001-5033-3848/work/63716983
dc.description.abstractWe study decision making in complex discrete-time dynamic environments where Bayesian optimization is intractable. A decision maker is equipped with a finite set of benchmark strategies. She aims to perform similarly to or better than each of these benchmarks. Furthermore, she cannot commit to any decision rule, hence she must satisfy this goal at all times and after every history. We find such a rule for a sufficiently patient decision maker and show that it necessitates not to rely too much on observations from distant past. In this sense we find that it can be optimal to forget.
dc.relation.ispartofJournal of Economic Theoryen
dc.rights© 2017 Elsevier Inc. All rights reserved. This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at:
dc.subjectDynamic consistencyen
dc.subjectForecast combinationen
dc.subjectNon-Bayesian decision makingen
dc.subjectRegret minimizationen
dc.subjectHB Economic Theoryen
dc.subjectEconomics and Econometricsen
dc.titleDynamic benchmark targetingen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Economics and Financeen
dc.description.statusPeer revieweden

This item appears in the following Collection(s)

Show simple item record